Senior Data Engineer

Position Overview

We are seeking an experienced Senior Data Engineer to serve as a technical leader responsible for architecting systems within your team's domain and driving complex, cross-team projects that directly support our cybersecurity platform's strategic objectives. This role requires someone who can architect systems within your team's domain, reasonably be expected to come up with and drive the projects that your crew should do to solve complex business problems, and actively mentor other engineers.

As a Senior Data Engineer, you will fully understand and own multiple entire areas of the codebase or multiple services, work with your Manager or a Technical Director to validate your technical decisions when you ask for input, and contribute significantly to our data engineering practices and standards.

Essential Qualifications (All Required)

• Bachelor's degree in Computer Science, Data Engineering, or related technical field (Master's degree preferred)
• Minimum 6-10 years of hands-on data engineering experience in large-scale, high-volume environments
• Expert proficiency in at least one of SQL and Python, with strong understanding of the other
• Extensive experience with Snowflake architecture, optimization, and performance tuning
• Demonstrated experience building Kimball dimensional data warehouses and star schema architectures
• Strong AWS cloud infrastructure experience with focus on data operations
• Production experience with either DBT or SQLMesh for data transformation workflows
• Experience with CI/CD pipelines, GitFlow/trunk-based development, and data governance frameworks
• Knowledge of compliance requirements (GDPR, PCI-DSS) in data systems
• Proven ability to architect systems that are within your team's domain on your own

Advanced Technical Requirements

• Streaming & Real-time Processing: Experience with Apache Kafka, event-driven architectures, and real-time analytics pipelines
• Modern Data Architecture: Familiarity with Apache Iceberg, data lakehouse architectures, and modern table formats
• Performance Optimization: Experience with data warehouse performance tuning and cost optimization practices

Domain Expertise (Preferred)

• Subscription Business Models: Experience with cohort analysis, LTV calculations, churn prediction, or marketing attribution frameworks
• High-Volume Industries: Experience in cybersecurity, ad-tech, fintech, or similar industries processing large volumes of data
• Complex Analytics: Experience building feature usage analytics, behavioral analysis, or executive reporting systems

Key Responsibilities

Technical Leadership & Project Ownership

• Cross-Team Projects: Lead projects that cross teams, actively working with your Manager to set the technical vision for your team
• Problem Solving: Be handed a problem and reasonably be expected to come up with and drive the projects that your crew should do to solve that problem
• System Architecture: Architect systems that are within your team's domain, with guidance from Manager or Technical Director when needed

Implementation & Development

• Domain Ownership: Fully understand and own multiple entire areas of the codebase or multiple services
• Technology Integration: Lead evaluation and implementation of new technologies that benefit your team's domain
• Quality Standards: Ensure all work meets our high-quality pull request standards and follows established engineering processes

Collaboration & Mentoring

• Cross-Functional Collaboration: Collaborate across teams inside the Data Engineering org, represent your team as needed, and reach out to external stakeholders for clarifications
• Mentoring: Actively mentor IC7s and IC8s, focusing on adopting our processes, technical knowledge, and quality of execution
• Stakeholder Engagement: Work with engineers in the rest of Gen to help move the org forward

Quantifiable Performance Expectations

• Technical Output: Minimum 4+ PRs per week (GitFlow) or 6+ PRs per week (Trunk-based development)
• Code Reviews: 2+ comprehensive reviews per day from anyone in the areas/services you contribute to
• Documentation: Author at least 1+ RFC or Tech Spec per year that demonstrates technical leadership
• Meeting Efficiency: No more than 15% of work hours spent in meetings to maintain focus on technical work
• Deployments: Routinely deploy to production with appropriate oversight and process adherence

Technical Competency Expectations

• Domain Knowledge: Extremely knowledgeable in your domains and able to almost always help anyone coming to you with technical questions
• Development Skills: Expert in at least one of SQL and Python, with strong understanding of the other enough to be an effective IC10
• Process Excellence: Very reliably follow our processes with code that only requires revisions for architectural reasons
• Architecture Understanding: Contribute to the architecture of systems within your team's domain
• Collaboration: Collaborate across teams inside the Data Engineering org and represent your team to external stakeholders when needed

Career Impact & Growth

This role represents a senior individual contributor position within our Data Engineering organization where you'll have the opportunity to:

• Lead Technical Projects: Drive complex, cross-team initiatives that solve important business problems
• Mentor Junior Engineers: Help develop the next generation of data engineering talent through active mentoring
• Shape Team Standards: Contribute to establishing and maintaining high engineering standards within your domain
• Solve Complex Problems: Work on challenging technical problems that require deep expertise and creative solutions
• Collaborate Across Teams: Build relationships and work effectively with stakeholders across the Data Engineering organization

This position is ideal for an experienced data engineering professional who wants to take on significant technical leadership responsibilities, enjoys mentoring others, and thrives on solving complex data challenges in a high-growth cybersecurity environment.

Gen is proud to be an equal-opportunity employer, committed to diversity and inclusivity. We base employment decisions on merit, experience, and business needs, without considering race, color, national origin, age, religion, sex, pregnancy, genetic information, disability, medical condition, marital status, sexual orientation, gender identity or expression, military or veteran status, or other unlawful factors. Gen prohibits discrimination based on these protected characteristics and recruits talented candidates from diverse backgrounds.

We consider individuals with arrest and conviction records and do not discriminate against employees for discussing their own pay or that of other employees or applicants. Learn more about pay transparency. 

To conform to U.S. export control regulations, applicant should be eligible for any required authorizations from the U.S. Government.